Model predictive control using fuzzy decision functions

da Costa Sousa, JM; Kaymak, U

Abstract

Abstract—Fuzzy predictive control integrates conventional
model predictive control with techniques from fuzzy multicriteria
decision making, translating the goals and the constraints to predictive
control in a transparent way. The information regarding
the (fuzzy) goals and the (fuzzy) constraints of the control problem
is combined by using a decision function from the theory of fuzzy
sets. This paper investigates the use of fuzzy decision making
(FDM) in model predictive control (MPC), and compares the
results to those obtained from conventional MPC. Attention is
also paid to the choice of aggregation operators for fuzzy decision
making in control. Experiments on a nonminimum phase, unstable
linear system, and on an air-conditioning system with nonlinear
dynamics are studied. It is shown that the performance of the
model predictive controller can be improved by the use of fuzzy
criteria in a fuzzy decision making framework.

Citation

da Costa Sousa, J., & Kaymak, U. Model predictive control using fuzzy decision functions

• Journal Article Type: Article
• Deposit Date: Mar 12, 2009
• Publicly Available Date: Mar 12, 2009
• Journal: IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics
• Print ISSN: 10834419
• Peer Reviewed: Peer Reviewed
• Volume: 31
• Issue: 1
• Pages: 54-65
• Keywords: Fuzzy criteria, fuzzy decision making (FDM),; fuzzy predictive control, model predictive control (MPC)
• Publisher URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=00907564
• Related Public URLs: http://ieeexplore.ieee.org/Xplore/dynhome.jsp